Incorporating static intersite correlation effects in vanadium dioxide through DFT$+V$

TL;DR

This paper enhances the DFT+V method by incorporating intersite correlations to better model the structural and electronic phase transition in VO$_2$, capturing its insulating monoclinic phase more accurately.

Contribution

The study introduces an empirical inter-atomic potential within DFT+V, improving the modeling of VO$_2$'s phase transition and electronic properties with computational efficiency.

Findings

Intersite V enhances band splitting and promotes dimerization.

Monoclinic phase becomes the global energy minimum with V.

Transition sharpness increases with higher V.

Abstract

We analyze the effects on the structural and electronic properties of vanadium dioxide (VO$_2$) of adding an empirical inter-atomic potential within the density-functional theory$+V$ (DFT$+V$) framework. We use the DFT$+V$ machinery founded on the extended Hubbard model to apply an empirical self-energy correction between nearest-neighbor vanadium atoms in both rutile and monoclinic phases, and for a set of structures interpolating between these two cases. We observe that imposing an explicit intersite interaction $V$ along the vanadium-vanadium chains enhances the characteristic bonding-antibonding splitting of the relevant bands in the monoclinic phase, thus favoring electronic dimerization and the formation of a band gap. We then explore the effect of $V$ on the structural properties and the relative energies of the two phases, finding an insulating global energy minimum for the monoclinic phase, consistent with experimental observations. With increasing $V$, this minimum becomes deeper relative to the rutile structure, and the transition from the metallic to the insulating state becomes sharper. We also analyze the effect of applying the $+V$ correction either to all or only to selected vanadium-vanadium pairs, and both in the monoclinic as well as in the metallic rutile phase. Our results suggest that DFT$+V$ can indeed serve as a computationally inexpensive unbiased way of modeling VO$_2$ which is well suited for studies that, e.g., require large system sizes.